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At least 73 records · Page 4

Slow manifolds of classical Pauli particle enable structure-preserving geometric algorithms for guiding center dynamics

Since variational symplectic integrators for the guiding center was proposed, structure-preserving geometric algorithms have become an active research field in plasma physics. We found that the slow manifolds of the classical Pauli particle enable a family of structure-preserving geometric algorithms for guiding center dynamics with long-term stability and accuracy. This discovery overcomes the difficulty associated with the unstable parasitic modes for variational symplectic integrators when applied to the degenerate guiding center Lagrangian. It is a pleasant surprise that Pauli's Hamiltonian for electrons, which predated the Dirac equation and marks the beginning of particle physics, reappears in classical physics as an effective algorithm for solving an important plasma physics problem. This technique is applicable to other degenerate Lagrangians reduced from regular Lagrangians.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A review of collaborative studies between the NSTX/-U and MAST/-U spherical tokamaks

The National Spherical Torus Experiment (NSTX) at the Princeton Plasma Physics Laboratory in the United States, and the mega ampere spherical tokamak (MAST) at the United Kingdom Atomic Energy Authority in the United Kingdom, and their respective upgrades (NSTX-U and MAST-U) are two MAST fusion devices that have operated roughly over the past two decades. Both devices have made significant contributions to understanding spherical tokamak (ST) plasma physics, and fusion plasmas in general, and both have contributed data to multi-machine database studies. Several diagnostics have been physically moved from one machine to the other by diagnostic teams working on both devices. Collaboration has benefited both research teams in the areas of operational expertise, scenario development, and equilibrium reconstruction techniques. More focused comparative studies between the two devices have been pursued over the years in many areas as well, including stability calculations, disruption characterization, pedestal and edge localized mode stability, confinement and transport, energetic particles, and heating and current drive modelling. Together NSTX/-U and MAST/-U set the stage for the future of STs, which is entering the phase of design of demonstration power plant devices.

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Simulating nonlinear optical processes on a superconducting quantum device

Simulating plasma physics on quantum computers is difficult because most problems of interest are nonlinear, but quantum computers are not naturally suitable for nonlinear operations. In weakly nonlinear regimes, plasma problems can be modelled as wave–wave interactions. In this paper, we develop a quantization approach to convert nonlinear wave–wave interaction problems to Hamiltonian simulation problems. We demonstrate our approach using two qubits on a superconducting device. Unlike a photonic device, a superconducting device does not naturally have the desired interactions in its native Hamiltonian. Nevertheless, Hamiltonian simulations can still be performed by decomposing required unitary operations into native gates. To improve experimental results, we employ a range of error-mitigation techniques. Apart from readout error mitigation, we use randomized compilation to transform undiagnosed coherent errors into well-behaved stochastic Pauli channels. Moreover, to compensate for stochastic noise, we rescale exponentially decaying probability amplitudes using rates measured from cycle benchmarking. We carefully consider how different choices of product-formula algorithms affect the overall error and show how a trade-off can be made to best utilize limited quantum resources. This study provides an example of how plasma problems may be solved on near-term quantum computing platforms.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Roadmap for warm dense matter physics

This roadmap presents the state-of-the-art, current challenges and near future developments anticipated in the thriving field of warm dense matter physics. Originating from strongly coupled plasma physics, high pressure physics and high energy density science, the warm dense matter physics community has recently taken a giant leap forward. This is due to spectacular developments in laser technology, diagnostic capabilities, and computer simulation techniques. Only in the last decade has it become possible to perform accurate enough simulations \& experiments to truly verify theoretical results as well as to reliably design experiments based on predictions. Consequently, this roadmap discusses recent developments and contemporary challenges that are faced by theoretical methods, and experimental techniques needed to create and diagnose warm dense matter. A large part of this roadmap is dedicated to specific warm dense matter systems and applications in astrophysics, inertial confinement fusion and novel material synthesis.

FOS: Physical sciences↗

Dense plasma opacity via the multiple-scattering method

The calculation of the optical properties of hot dense plasmas with a model that has self-consistent plasma physics is a grand challenge for high energy density science. Here we exploit a recently developed electronic structure model that uses multiple scattering theory to solve the Kohn-Sham density functional theory equations for dense plasmas. Here we calculate opacities in this regime, validate the method, and apply it to recent experimental measurements of opacity for Cr, Ni, and Fe. Good agreement is found in the quasicontinuum region for Cr and Ni, while the self-consistent plasma physics of the approach cannot explain the observed difference between models and the experiment for Fe.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Absolute Neutron Rate Measurement and Non-Thermal/Thermonuclear Fusion Differentiation

The goal of fusion energy is to produce significantly more energy from fusion reactions than is input into the device. One of the products of fusion reactions is neutrons, which, due to their lack of charge, provide a unique view into the parameters of the device. Lawrence Livermore National Laboratory (LLNL) in collaboration with the University of California, Berkeley (UCB) have designed, assembled, and fielded a robust and portable neutron detection system known as PANDA (Portable and Adaptable Neutron Diagnostics for ARPA-E). This detector suite consists of three LaBr activation detectors that are calibrated to give a total neutron yield on shot, and twenty-four scintillators coupled to photo-multiplier tubes (SPMT). The SPMTs can be configured to attain spatial, temporal and/or energy information from fusion neutrons. The system was designed to be portable and is compartmentalized so that individual components can be used at different fusion facilities. During the duration of this work, part of the system was installed at the FuZE facility, a part of Zap Energy. Another component was installed that the CESZAR facility at the University of California, San Diego (UCSD) to support experiments by Magneto-Inertial Fusion Technologies, Inc. (MIFTI). The diagnostics were successful at both locations and the LLNL/UCB team supported the data analysis by creating and running analysis scripts and Monte-Carlo calculations. At Zap Energy the diagnostics demonstrated that the fusion from the FuZE device is thermonuclear in nature, a result that resulted in an invited talk at the American Physical Society Division of Plasma Physics and an invited paper. Additionally, temporal and spatial data was taken using the SPMTs to understand the duration and length of fusion production. At UCSD the neutron yield from the diagnostics was used to show improvements to fusion yields on their gas puff Z-pinch when using a gas shell surrounding the fuel. The success in this diagnostic has led to continued work at both Zap Energy and MIFTI, as well as follow on funding and interest at other fusion energy companies.

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Transfer learning nonlinear plasma dynamic transitions in low dimensional embeddings via deep neural networks

Deep learning algorithms provide a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. Development of novel, data-driven model reduction methods, coupled with detection of abnormal modes with plasma physics, opens a unique opportunity to identify plasma instabilities through automated construction of parsimonious models that can be tuned to balance accuracy and cost. Our fusion transfer learning (FTL) model demonstrates success in rapidly reconstructing nonlinear kink mode structures by learning from a limited amount of nonlinear simulation data. The knowledge transfer process leverages a pre-trained neural encoder–decoder network, initially trained on linear simulations, to effectively capture nonlinear dynamics. The low-dimensional embeddings extract the coherent structures of interest, while preserving the inherent dynamics of the complex system. Experimental results highlight FTL’s capacity to capture transitional behaviors and dynamical features in plasma dynamics—a task often challenging for conventional methods. The model developed in this study is generalizable and can be extended broadly through transfer learning to address various magnetohydrodynamics modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

COMPASS-U Global Heat Balance Calculations

COMPASS-U is a medium size, high magnetic field experimental tokamak (R = 0.9 m, B t = 5 T, and I p = 2 MA), built at the Institute of Plasma Physics, Czech Academy of Sciences (IPP-CAS). This global heat balance calculation for COMPASS-U was done at Princeton Plasma Physics Laboratory (PPPL). Based on our previous experience of building global thermal model for National Spherical Torus Experiment-Upgrade (NSTX-U) at PPPL, this 2-D global thermal model geometry represents a typical cross section of COMPASS-U machine. The model includes thermal radiation, conduction, and convection among components and also between the machine and outer environment. Helium gas heating/cooling was modeled with fluid element and surface element. This model was used to calculate component temperatures and heat distribution during heat up, cryogenic cool down, normal operation, and fault operation scenarios. Definition of 14 main thermal scenarios was provided by IPP-CAS. First nine are normal operation scenarios. Scenarios #10–#14 are fault scenarios. Results of thermal scenario #5 will be given and discussed in this article, including peak temperatures, temperature ratcheting, energy distribution, and required cooling power.

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Slow manifold reduction for plasma science

The classical Chapman–Enskog procedure admits a substantial geometrical generalization known as slow manifold reduction. This generalization provides a paradigm for deriving and understanding most reduced models in plasma physics that are based on controlled approximations applied to problems with multiple timescales. In this Review we develop the theory of slow manifold reduction with a plasma physics audience in mind. In particular we illustrate (a) how the slow manifold concept may be used to understand breakdown of a reduced model over sufficiently-long time intervals, and (b) how a discrete-time analogue of slow manifold theory provides a useful framework for developing implicit integrators for temporally-stiff plasma models. For readers with more advanced mathematical training we also use slow manifold reduction to explain the phenomenon of inheritance of Hamiltonian structure in dissipation-free reduced plasma models. Various facets of the theory are illustrated in the context of the Abraham–Lorentz model of a single charged particle experiencing its own radiation drag. As a culminating example we derive the slow manifold underlying kinetic quasineutral plasma dynamics up to first-order in perturbation theory. This first-order result incorporates several physical effects associated with small deviations from exact charge neutrality that lead to slow drift away from predictions based on the leading-order approximation n e = Z i n i .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

MHD Analysis of Dual-Coolant Lead-Lithium Blanket for Spherical Tokamak Advanced Reactor

The tritium breeding blanket is vital for future fusion power plants, with the Spherical Tokamak Advanced Reactor (STAR) project highlighting the dual-coolant lead-lithium (DCLL) design. The DCLL blanket performs shielding, energy exhaust, and tritium breeding using a lead-lithium alloy , with lithium as the breeder and lead as the neutron multiplier. It also serves as the primary coolant, with helium providing supplemental cooling. Reduced-activation ferritic/martensitic steel is used for the blanket structure. Magnetohydrodynamic (MHD) phenomena influence the liquid metal flow in a magnetic field, affecting heat transfer in the breeder affected by energetic neutrons. Understanding key flow parameters in such conditions is critical for efficient DCLL design. This study uses three-dimensional thermofluid MHD analysis with ANSYS CFX software, modified at Princeton Plasma Physics Laboratory, to simulate high Hartmann flows. The neutronics code MCNP, coupled with plasma equilibrium, provides heat source distribution. In conclusion, we examine electromagnetic interactions in adjacent fluid domains and analyze the magnetic field’s impact on flow distribution in the inboard and outboard blanket layout, using detailed mesh generation for accurate results.

DCLL↗

Solving the auroral-arc-generator question by using an electron beam to unambiguously connect critical magnetospheric measurements to auroral images

Here, an active mapping mission is described that unambiguously connects measurements in the Earth's magnetosphere to visible aurora in the atmosphere. The core of the mission is an electron-beam source operated on a spacecraft in the equatorial magnetosphere, with the electron beam traveling along the Earth's magnetic-field lines to the atmosphere, depositing its energy to create an optical beam-spot in the atmosphere at the footpoint of the spacecraft's magnetic-field line. This optical spot can be imaged by ground-based cameras, putting the location of the spacecraft's magnetic footpoint into the context of the optical aurora. Scientific instruments carried on the spacecraft make critical measurements of the properties of the magnetosphere at the locations where the magnetosphere powers the aurora, allowing the determination of the plasma-physics mechanisms by which the magnetosphere drives the aurora, in particular answering the outstanding question of how the magnetosphere drives low-latitude auroral arcs. Long-standing questions in magnetosphere-ionosphere coupling that have not been answered because we could not unambiguously connect locations in the magnetosphere with their image in the ionosphere will finally be addressed. In this paper the properties of a “standard” growth-phase auroral arc are collected, theories of the magnetospheric generation of auroral arcs are reviewed, and critical magnetospheric measurements to discern the mechanisms that drive auroral arcs are determined. Further, the plasma physics of the experiment is investigated, including spacecraft-charging mitigation, beam stability, beam scattering, and electron orbit theory. Tradeoffs (keV versus MeV) concerning the energy of the electron beam are enumerated.

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Fluid-Kinetic Coupling: Advanced Discretizations for Simulations on Emerging Heterogeneous Architectures (LDRD FY20-0643)

Plasma physics simulations are vital for a host of Sandia mission concerns, for fundamental science, and for clean energy in the form of fusion power. Sandia's most mature plasma physics simulation capabilities come in the form of particle-in-cell (PIC) models and magnetohydrodynamics (MHD) models. MHD models for a plasma work well in denser plasma regimes when there is enough material that the plasma approximates a fluid. PIC models, on the other hand, work well in lower-density regimes, in which there is not too much to simulate; error in PIC scales as the square root of the number of particles, making high-accuracy simulations expensive. Real-world applications, however, almost always involve a transition region between the high-density regimes where MHD is appropriate, and the low-density regimes for PIC. In such a transition region, a direct discretization of Vlasov is appropriate. Such discretizations come with their own computational costs, however; the phase-space mesh for Vlasov can involve up to six dimensions (seven if time is included), and to apply appropriate homogeneous boundary conditions in velocity space requires meshing a substantial padding region to ensure that the distribution remains sufficiently close to zero at the velocity boundaries. Moreover, for collisional plasmas, the right-hand side of the Vlasov equation is a collision operator, which is non-local in velocity space, and which may dominate the cost of the Vlasov solver. The present LDRD project endeavors to develop modern, foundational tools for the development of continuum-kinetic Vlasov solvers, using the discontinuous Petrov-Galerkin (DPG) methodology, for discretization of Vlasov, and machine-learning (ML) models to enable efficient evaluation of collision operators. DPG affords several key advantages. First, it has a built-in, robust error indicator, allowing us to adapt the mesh in a very natural way, enabling a coarse velocity-space mesh near the homogeneous boundaries, and a fine mesh where the solution has fine features. Second, it is an inherently high-order, high-intensity method, requiring extra local computations to determine so-called optimal test functions, which makes it particularly suited to modern hardware in which floating-point throughput is increasing at a faster rate than memory bandwidth. Finally, DPG is a residual-minimizing method, which enables high-accuracy computation: in typical cases, the method delivers something very close to the $L^2$ projection of the exact solution. Meanwhile, the ML-based collision model we adopt affords a cost structure that scales as the square root of a standard direct evaluation. Moreover, we design our model to conserve mass, momentum, and energy by construction, and our approach to training is highly flexible, in that it can incorporate not only synthetic data from direct-simulation Monte Carlo (DSMC) codes, but also experimental data. We have developed two DPG formulations for Vlasov-Poisson: a time-marching, backward-Euler discretization and a space-time discretization. We have conducted a number of numerical experiments to verify the approach in a 1D1V setting. In this report, we detail these formulations and experiments. We also summarize some new theoretical results developed as part of this project (published as papers previously): some new analysis of DPG for the convection-reaction problem (of which the Vlasov equation is an instance), a new exponential integrator for DPG, and some numerical exploration of various DPG-based time-marching approaches to the heat equation. As part of this work, we have contributed extensively to the Camellia open-source library; we also describe the new capabilities and their usage. We have also developed a well-documented methodology for single-species collision operators, which we applied to argon and demonstrated with numerical experiments. We summarize those results here, as well as describing at a high level a design extending the methodology to multi-species operators. We have released a new open-source library, MLC, under a BSD license; we include a summary of its capabilities as well.

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Collaborative Research: Explosive reconnection in relativistic magnetically-dominated plasmas (Final Report)

Magnetic fields can be the dominant component of astrophysical plasmas, so that the magnetic energy density might exceed even the rest-mass energy density of matter. In this extreme (and largely unexplored) regime the magnetic field controls the overall plasma evolution, dissipation, and acceleration of non-thermal particles. This plasma regime, applicable to a variety of astrophysical sources - magnetars, pulsars and pulsar wind nebulae (PWNe), jets of Active Galactic Nuclei (AGNs) and Gamma-Ray Bursters (GRBs) - is dramatically different from laboratory plasmas, the magnetospheres of planets, and the interplanetary plasma. Relativistic astrophysical sources then provide an unique opportunity to study the fundamental plasma physics of magnetically-dominated plasmas; a novel and fast-evolving field of theoretical research which, by investigating energy conversion and particle energization processes in plasmas, is of vital importance to the Fusion Energy Sciences DoE program. Data coming from astrophysical high-energy missions, especially the Crab Nebula flares recently observed by the Fermi and AGILE satellites, suggest that the acceleration of non-thermal particles to the highest energies occurs in magnetic reconnection events - a major change of paradigm in high-energy astrophysics. Most importantly, observations demand that particle acceleration should proceed extremely fast (with accelerating electric field of the order of the magnetic field) and on macroscopic scales (much larger, e.g., than the microscopic plasma skin depth). We are conducting studies of the microphysics of magnetically-dominated plasmas focussing in particular on the highly dynamic regime of explosive reconnection and associated particle acceleration in relativistic plasmas. We are studying the stability and explosive plasma dynamics, particle acceleration and radiation production in a number of idealized plasma configurations that approximate relevant astrophysical sources (like the magnetic ABC structures and interacting flux tubes, as well as generalizations of analytical models of X-point collapse to relativistic plasmas). The well-studied case of the Crab Nebula is taken as a prototypical example for the application of the model. We are combining analytical studies of explosive magnetic dynamics and dissipation in relativistic plasmas with particle-in-cell (PIC) simulations and fluid simulations. The theoretical model, fluid and particle-in-cell simulations are cross-checked for agreement and convergence.

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Reflection and transmission of electromagnetic pulses at a planar dielectric interface -- theory and quantum lattice simulations

There is considerable interest in the application of quantum information science to advance computations in plasma physics. A particular point of curiosity is whether it is possible to take advantage of quantum computers to speed up numerical simulations relative to conventional computers. Many of the topics in fusion plasma physics are classical in nature. In order to implement them on quantum computers it will require couching a classical problem in the language of quantum mechanics. Electromagnetic waves are routinely used in fusion experiments to heat a plasma or to generate currents in the plasma. The propagation of electromagnetic waves is described by Maxwell equations with an appropriate description of the plasma as a dielectric medium. Before advancing to the tensor dielectric of a magnetized plasma, this paper considers electromagnetic wave propagation in a one-dimensional inhomogeneous scalar dielectric. The classic theory of scattering of plane electromagnetic waves at a planar interface, separating two different dielectric media, leads to Fresnel equations for reflection and transmission coefficients. In contrast to plane waves, this paper is on the reflection and transmission of a spatially confined electromagnetic pulse. Following an analytical formulation for the scattering of a Gaussian pulse, it is deduced that the maximum transmission coefficient for a pulse is $\sqrt{n_2/n_1}$ times that for a plane wave; the incident and transmitted pulses propagating in dielectric media with refractive indices $n_1$ and $n_2$, respectively. The analytical theory is complemented by numerical simulations using a quantum lattice algorithm for Maxwell equations. The algorithm, based on the Riemann-Silberstein-Weber representation of the electromagnetic fields and expressed in term of qubits, is an interleaved sequence of entangling operators at each lattice site and unitary streaming operators which transmit information from one site to an adjacent lattice site. Besides substantiating results from the theory for Gaussian pulses, numerical simulations show their validity for non-Gaussian pulses. Apart from their time-asymptotic forms, the simulations display an interplay between the incident, reflected, and transmitted pulses in the vicinity of the transition region between two dielectric media.

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LLNL FESP Theory Highlights: October 2024

I. Novikau, I. Y. Dodin, E. A. Startsev, I. Joseph, Quantum algorithms for simulating dissipative linear and nonlinear dynamics of plasmas. Invited talk at the 66th Annual Meeting of the APS Division of Plasma Physics, Atlanta, Georgia. Novikau I., Dodin I.Y., Startsev E.A., Encoding of linear kinetic plasma problems in quantum circuits via data compression, Journal of Plasma Physics. 2024;90(4):805900401, doi:10.1017/S0022377824000795. We propose an algorithm for encoding linear kinetic plasma problems in quantum circuits. The focus is on modelling electrostatic linear waves in a one-dimensional Maxwellian electron plasma. The waves are described by the linearized Vlasov–Ampère system with a spatially localized external current that drives plasma oscillations. This system is formulated as a boundary-value problem and cast in the form of a linear vector equation to be solved by using the quantum signal processing algorithm. The latter requires encoding of a matrix in a quantum circuit as a sub-block of a unitary matrix. We propose how to encode in a circuit in a compressed form and discuss how the resulting circuit scales with the problem size and the desired precision.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Unraveling the intrinsic atomic physics behind x-ray absorption line shifts in warm dense silicon plasmas

Here, we present a novel free-energy density functional theory (DFT)-based methodology for optical property calculations of warm dense matter to cover a wide range of thermodynamic conditions and photon energies including the entire x-ray range. It uses Mermin–Kohn–Sham density functional theory with exchange-correlation (XC) thermal effects taken into account via a fully temperature dependent generalized gradient approximation XC functional. The methodology incorporates a combination of the ab initio molecular dynamics (AIMD) snapshotted Kubo–Greenwood optic data with a single-atom in simulation cell calculations to close the photon energy gap between the L and K edges and extend the K-edge tail toward many-keV photon energies. This gap arises in the standard scheme due to a prohibitively large number of bands required for the Kubo–Greenwood calculations with AIMD snapshots. Kubo–Greenwood data on snapshots provide an accurate description of optic properties at low photon frequencies slightly beyond the L-edge and x-ray absorption near edges structure (XANES) spectra, while data from periodic calculations with single atoms cover the tail regions beyond the edges. To demonstrate its applicability to mid-Z materials where the standard DFT-based approach is not computationally feasible, we have applied it to opacity calculations of warm dense silicon plasmas. These first-principles calculations revealed a very interesting phenomon of red-to-blue shift in K–L (1s → 2p) and K-edge absorptions along both isotherm and isochore, which are absent in most continuum-lowering models of traditional plasma physics. This new physics phenomenon can be attributed to the underlying competition between the screening of deeply bound core electrons and the screening of outer-shell electrons caused by warm-dense-plasma conditions. We further demonstrate that the ratio of 1s → 2p to the K-edge x-ray absorptions can be used to characterize warm-dense-plasma conditions. Eventually, based on our absorption calculations, we have established a first-principles opacity table (FPOT) for silicon in a wide range of material densities and temperatures.

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Effects of plasma on physical properties of water: nanocrystalline-to-amorphous phase transition and improving produce washing

Recently is was discovered in various applications that many physical and chemical properties of water change their temperature dependence between about 35 and 60 degrees Celsius. In particular, heat conductance, light absorption, and surface tension all change their temperature dependence. These drastic changes were associated with water gradually changing its mesoscopic structure: while at the higher temperatures water is a uniform media (amorphous state), at the temperatures below transition it consists of many nano-to-micro-scale clusters (crystalline state). This transition is similar to the second order phase transition. In the present paper we show that treating water with non-thermal plasma (adding plasma-created active compounds) can lower the temperature of the transition and thus cause a significant change in such physical quantities as surface tension, viscosity, freezing rate, and wettability and washability. We present analytical estimates of the transition temperature shift based on the Debye-Hückel theory. We discuss the produce-washing experiments that illustrate the predicted effects.

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